Abstract

State Retail Sukuk is a Sharia Securities issued and its sale is regulated by the State, namely the Ministry of Finance (Depkeu). Where the government will choose the seller agent and consulting retail sukuk law. Selling agents must be obliged to have a commitment to the government in the development of the sukuk market and experience in selling Islamic financial products. The publication of this instrument is likened to a "mutualist symbiosis" between the Government and Society, both of which benefit equally. The government as the publisher benefits from the use of funds from the community, while the community benefits from investments made. This research contributes to the government and the Bank to be able to promote maximally for the next sukuk issuer. The data used is data from kemenkeu through website www.djppr.kemenkeu.go.id. The data are sukuk sales data with series 001 - 007 which are grouped into several categories namely geography, profession and age category. Algorithm used in this research is Artificial Neural Network with Backpropogation method. The input variables used are PNS (X1), Private Officer (X2), IRT (X3), Entrepreneur (X4), TNI / Polri (X5) and Others (X6) with architectural model of training and testing of 6 architectures 6-2-1, 6-5-1, 6-2-5-1 and 6-5-2-1. The output (output) generated is the best pattern of the ANN architecture. The best architectural model is 6-5-2-1 with epoch 37535, MSE 0.0009997295 and 100% accuracy rate. From this model will be conducted sensitivity analysis to see the variable that has the best performance and obtained variable Private Employees (X2) with a score of 0.3268. So obtained the results of the most investors predicted on the purchase of sukuk for the next 008 series based on the profession category is Private Employees.